Random Subspace Two-Dimensional PCA for face recognition

The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA method in recognising human face. However, in many cases, this method tends to be overfitted to sample data. In this paper, we proposed a novel method named random subspace two-dimensional PCA (RS-2DPCA), which combines the 2DPCA method with the random subspace (RS) technique. The RS-2DPCA inherits the advantages of both the 2DPCA and RS technique, thus it can avoid the overfitting problem and achieve high recognition accuracy. Experimental results in three benchmark face data sets -the ORL database, the Yale face database and the extended Yale face database B - confirm our hypothesis that the RS-2DPCA is superior to the 2DPCA itself.

Hierarchical semi-markov conditional random fields for recursive sequential data

Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov chains to model complex hierarchical, nested Markov processes. It is parameterised in a discriminative framework and has polynomial time algorithms for learning and inference. Importantly, we develop efficient algorithms for learning and constrained inference in a partially-supervised setting, which is important issue in practice where labels can only be obtained sparsely. We demonstrate the HSCRF in two applications: (i) recognising human activities of daily living (ADLs) from indoor surveillance cameras, and (ii) noun-phrase chunking. We show that the HSCRF is capable of learning rich hierarchical models with reasonable accuracy in both fully and partially observed data cases.

Utility-based summarization of home videos

The aim of this work is to devise an effective method for static summarization of home video sequences. Based on the premise that the user watching a summary is interested in people related (how many, who, emotional state) or activity related aspects, we formulate a novel approach to video summarization that works to specifically expose relevant video frames that make the content spotting tasks possible. Unlike existing approaches, which work on low-level features which often produce the summary not appealing to the viewer due to the semantic gap between low-level features and high-level concepts, our approach is driven by various utility functions (identity count, identity recognition, emotion recognition, activity recognition, sense of space) that use the results of face detection, face clustering, shot clustering and within cluster frame alignment. The summarization problem is then treated as the problem of extracting the set of key frames that have the maximum combined utility.

Utility-based quality of life associated with overweight and obesity : the Australian diabetes, obesity, and lifestyle study

This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00–1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (−0.008, 0.010) for overweight, −0.012 (−0.022, −0.001) for class-I obese, −0.020 (−0.041, 0.001) for class-II obese, and −0.069 (−0.099, −0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. Results confirmed an inverse dose–response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.

Utility of short-term evaluation of presbyopic contact lens performance

Objectives: To establish if evaluations of multifocal contact lens performance conducted at dispensing are representative of behavior after a moderate adaptation period.

Methods: Eighty-eight presbyopic subjects, across four clinical sites, wore each of four multifocal soft contact lenses (ACUVUE BIFOCAL, Focus Progressives, Proclear Multifocal, and SofLens Multifocal) for 4 days of daily wear. Comprehensive performance assessments were conducted at dispensing and after 4 days wear and included the following objective metrics: LogMAR acuity (contrast, 90% and 10%; illumination, 250 and 10 cd/m2; distance, 6 m, 100 cm, and 40 cm), stereopsis (RANDOT), reading critical print size and maximum speed and range of clear vision at near. Subjective assessments were made, with 100-point numerical rating scales, of comfort, ghosting (distance, near), visual quality (distance, intermediate, and near), and the appearance of haloes. At two sites, subjects (n = 39) also rated visual fluctuation (distance, intermediate, and near), facial recognition, and overall satisfaction.

Results: Among the objective variables, significant differences (paired t test, P<0.05) between dispensing and 4 days were found only for range of clear vision at near (2.9 ± 2.0 cm; mean difference ± standard deviation) and high contrast near acuity in low illumination (-0.013 ± 0.011 LogMAR). With the exception of insertion comfort, all subjective variables showed significant decrements over the same period. Overall satisfaction declined by an average of 10.9 ± 5.1 points.

Conclusions: Early assessment is relatively unrepresentative of performance later on during multifocal contact lens wear. Acuity based measures of vision remain substantially unchanged over the medium term, apparently because these metrics are insensitive indicators of performance compared with subjective alternatives.

Development and characterisation of 20 microsatellite loci isolated from the large bent-wing bat, Miniopterus schreibersii (Chiroptera: Miniopteridae) and their cross-taxa utility in the family Miniopteridae

The large bent-wing bat, Miniopterus schreibersii (Kuhl 1819), has a long history of taxonomic uncertainty and many populations are known to be in a state of decline. Microsatellite loci were developed for the taxonomic and population genetic assessment of the Australian complex of this species. Of the 33 primer sets designed for this research, seven (21%) were deemed suitably polymorphic for population-level analyses of the Australian taxa, with five (71%) of these loci revealing moderate to high levels of polymorphism (PIC = 0.56 to 0.91). The cross-taxa utility of the M. schreibersii microsatellite markers was assessed in the microbat (Chiroptera) family Miniopteridae. Sub-species and species covering the Miniopteridae’s global distribution (with the exception of the Middle East) were selected, numbering 25 taxa in total. Amplification was successful for 26 loci, of which 20 (77%) were polymorphic. High cross-taxa utility of markers was observed with amplification achieved for all taxa for between four (20%) and 20 (100%) loci, and polymorphism was considered moderate to high (PIC = 0.47–0.91) for 12 (60%) of these loci. The high cross-taxa utility of the microsatellites reported herein reveal versatile and cost-effective molecular markers, contributing an important genetic resource for the research and conservation of Miniopteridae species worldwide.

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, ‘hidden’ trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

Improving P2P IPTV random peers search through user similarity

With internet services to the end users becoming more homogenous, thus providing high bandwidth for all users, multimedia services such as IPTV to the public as a whole will finally become a reality, but even given the more abundant resources, IPTV architecture is far from being highly available due to technical limitations, we aim to provide a meaningful optimization in the P2P distribution model, which is currently based on a random structure bounded by high delays and low performance, by using channel probability, user's habits studies and users' similarity, in order to optimize one of the key aspects of IPTV which is the peers management, which directly reflects on resources and user's Quality of Experience.

Extending the analytical utility of acidic potassium permanganate chemiluminescence

The purpose of this work was to improve the analytical usefulness of acidic potassium permanganate chemiluminescence for the determination of various analytical compounds. This thesis also examined the fundamental chemistry involved with these types of reactions.

Dimensionality reduction of protein mass spectrometry data using random projection

Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Unfortunately, classification performance may degrade owing to the enormously high dimensionality of the data. This paper investigates the use of Random Projection in protein MS data dimensionality reduction. The effectiveness of Random Projection (RP) is analyzed and compared against Principal Component Analysis (PCA) by using three classification algorithms, namely Support Vector Machine, Feed-forward Neural Networks and K-Nearest Neighbour. Three real-world cancer data sets are employed to evaluate the performances of RP and PCA. Through the investigations, RP method demonstrated better or at least comparable classification performance as PCA if the dimensionality of the projection matrix is sufficiently large. This paper also explores the use of RP as a pre-processing step prior to PCA. The results show that without sacrificing classification accuracy, performing RP prior to PCA significantly improves the computational time.